Amazon reveals customers are returning to on-premises solutions. At Athena Intelligence, we've anticipated this shift. Our platform adapts to your infrastructure: Multi-cloud (AWS, Azure, Google Cloud) AWS GovCloud On-premises Cloud or on-prem, Athena works where you need it. #AIInnovation #CloudComputing #PrivateCloud #AWS https://lnkd.in/ei9kpWuA Source: AWS statement to UK https://lnkd.in/e6Dst3Ee
Athena Intelligence
Data Infrastructure and Analytics
New York, NY 1,405 followers
Experience Athena, a 24/7 Enterprise AI Analyst purpose-built to operate Olympus, an AI native analytics platform.
About us
Athena Intelligence has developed Olympus, the world's first AI-native analytics platform designed for seamless human-machine collaboration. Operated by Athena, a 24/7 Enterprise AI Data Analyst, Olympus empowers organizations to unlock the full potential of their data and drive intelligent decision-making. With Olympus, enterprise teams can accelerate their analytics workflows by leveraging the power of AI in co-pilot and auto-pilot modes. As a co-pilot, Athena learns your unique workflows, providing intelligent suggestions and automating tasks. When you're ready, you can confidently hand over the controls to Athena for autonomous execution, achieving unprecedented efficiency and uncovering hidden insights in your analytics processes.
- Website
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https://www.athenaintelligence.ai/
External link for Athena Intelligence
- Industry
- Data Infrastructure and Analytics
- Company size
- 2-10 employees
- Headquarters
- New York, NY
- Type
- Privately Held
- Founded
- 2022
- Specialties
- Artificial Intelligence, Business Intelligence, Predictive Analytics, Generative AI, Enterprise AI, Causal AI, Decision Intelligence, Machine Learning, Human-Machine Teaming Software, Real-Time Decision Automation, Cognitive Decision Support Systems, and Intelligent Decision Agents
Locations
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Primary
Get directions
New York, NY, US
Employees at Athena Intelligence
Updates
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The Athena Intelligence team is in full gear after customer meetings this week! Enjoying the west side highway thanks to our Starlink setup.
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Athena Intelligence founder Brendon Geils will be a judge at the upcoming E2B event in San Francisco. Who should he meet while in town?
🤝 Who to meet at the Code Interpreting 2.0 🧠 Make a team, and join the hackathon in San Francisco. 🌉 You can win cool prizes and get feedback and recognition for your project, but you also get to meet our inspiring judges and speakers from the AI space: 🔶 Vasek Mlejnsky - Founder and CEO of E2B (cloud runtime for agents) 🔶 Nate Sesti - Co-Founder at Continue (AI coding assistant) 🔶 Dillon Laird - Founding engineer at LandingAI (computer vision models) 🔶 Brendon Geils - Founder and CEO of Athena Intelligence (enterprise AI data analysis) 🔶 Fireworks AI team (LLMs inference) 🔶 Shawn "Swyx" Wang - Writer, Founder, Devtools Startup Advisor 🔶 Edge team (research & development lab) More judges and speakers will be announced. If you are in San Francisco, register via the link below 🔗 👇
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We are starting to look a lot more like an analyst!
Here are some previews of our AI meeting attendance interface and experience! Athena Intelligence can join Microsoft Teams, Google Meet, or Zoom meetings. This goes beyond a meeting recording device + AI summarization at the end. The user can toggle Athena from "Listen" mode to "Participate" mode—yes, she participates LIVE in the call. While in participate mode, Athena can be set to converse over Chat, Voice, or both. You can even adjust the participation threshold... how often Athena engages in the conversation. On the high end, Athena will only respond when she's asked to, and on the low end, she is encouraged to give her opinion often and even attempt to drive the conversation. After a call finishes, the meeting is available on the user's Drive to analyze the recording further.
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Performance Analysis for RedBull 2013-2024 🏎 Empower your team to learn from the past & make informed decisions in the future in the world of Formula One. Use Athena to generate predictive and trend analysis for RedBull's performance in the past 11 years. Build a predictive analytics model using Query and Notebooks. Determine performance trajectory and circuit-specific trends using Flows and Sheets.
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⚡ Incredible energy at last night’s event! ⚡ A BIG thank you to 645 Ventures for making the evening possible, and to our partners Tavily and LangChain for co-hosting a great conversation on the future of AI agents, agentic cognitive architectures, and examples in production. Special thanks to Vadym Barda of LangChain, Elaine Gao of Cohere, and our own Brendon Geils of Athena Intelligence for providing great product demos of agentic architectures and real world applications of AI agents. Our team had a blast connecting with fellow founders and engineers passionate about shaping the future of AI agents! 🚀
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Athena Intelligence reposted this
Athena Intelligence empowers enterprise analysts with an AI-native analytics platform. Since April, they’ve used Firecrawl to efficiently ingest and understand written content from across the web!
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Building and Executing F1 Flows! 🏎 Create and implement F1 workflows using Athena. With a number of flow components to choose from, you can create any complexity of workflow by choosing from a wide range of inputs, outputs, data sources, AI models, vector stores, and embeddings. Execute in Athena Sheets by a simply adding flows to your workbench and performing a drag-and-drop in Sheets to run the desired flow. We illustrate this by curating a comparative analysis on driver performance across the years 2013-2024 in Formula One races by extracting information about the drivers with the most wins and greatest number of fastest laps.
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🚀 Integrating Cube within Athena 🚀 Power your Data Querying capabilities using Athena, backed by Cube We start by setting up the integration and demonstrating a sample use case where we generate an overview of the total races participated in and the total points earned by each driver with details about the location, car number, and their position in the race. Powerful integrations with Cube help you easily query large amounts of data in seconds by either utilizing your existing semantic layer or enabling you to set one up for your existing data sources.